The PLOS Biology XV Collection: 15 Years of Exceptional Science Highlighted across 12 Months
Bibliographic record
Abstract
In October of 2018 PLOS Biology celebrated its 15-year anniversary.Our corpus includes foundational works in all aspects of the biological sciences, from cognitive neuroscience to conservation ecology.The editors, both staff and Academic, are extremely proud of the quality and breadth of science published in our journal.PLOS Biology has also played a pivotal role within the Open Access movement, which in the 15 years since our launch has exploded and continues to revolutionize science communication.We commemorated our anniversary with a year-long celebration.Each month, one of our hard-working and highly-respected Editorial Board Members contributed a blog post describing their favorite PLOS Biology article and its impact on the respective field.Here, we collect these posts and featured manuscripts, which can also be found in this Collection [1].These posts highlight the incredible diversity of science published in our journal.In addition to featuring our Research Articles, some of our Academic Editors chose to highlight nonstandard research content.Among the mix, Piali Sengupta wrote about an important article featuring negative results, which reshaped how we think about pheromone signaling.Andrew Read discussed one of the articles published in our Magazine section, which featured emerging and forward-thinking theory on possible unforeseen outcomes of novel therapies.Jonathan Kimmelman highlighted work from our Meta-Research section on the lack of rigor by ethical
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.105 | 0.047 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".